The proliferation of smart mobile devices is leading to an unprecedented increase in mobile data traffic, but the distribution of traffic is not uniform over time. Networks often observe significant variation in utilization levels, mainly triggered by diurnal patterns of human activity; e.g., networks see more utilization during days than nights, cellular base-stations are more loaded during mornings and late evenings in residential areas, whereas base-stations near commercial areas are busy during office hours, etc. In fact, there is high variation in the throughput that a given traffic flow achieves even at short time scales of a few seconds.
As such, delivery of digital content to mobile devices over a spectrum (such as 3G spectrum) carries costs for mobile network operators, over-the-top-providers, and end users. Mobile network operators provide bandwidth for delivery of data services. Cellular networks incur significant capital and operational costs, which are increasing significantly due to the rapidly growing demand. Also, cellular wireless spectrum is a scarce and increasingly expensive resource. Consequently, it is important for the operators to extract the maximum yield out of the spectrum owned. In other words, it is important to minimize the times during which the network remains under-utilized.
Conventional solutions to the problem of reducing spectrum under-utilization have involved reducing the overall network service price, to result in cheaper subscription plans. While this might increase the adoption of services, it also ends up increasing logistical challenges and difficulties, such as increased contention during peak times, and can lead to a decrease in quality of experience (QoE).